ID 原文 译文
45446 并以智能驾驶、工业物联网这 2 个示范应用为例指出了当前雾计算在实际应用上仍需攻关的重要课题。 Taking the intelligent driving and industrial Internet of things applications as examples, the key research issues of fog computing were proposed.
45447 传统云计算用户信誉的研究主要集中在对用户操作行为信誉评估， Traditional cloud computing trust models mainly focused on the calculation of the trust of users’ behavior.
45448 较少涉及用户发布文本信息的安全管理，并且存在指标筛选欠准确、信誉评估结果缺乏科学验证等问题，难以满足监管部门的实际需求。 In the process of classification and evaluation, there were some problems such as ignorance of content security and lack of trust division verification.
45449 针对以上问题，提出基于评分卡—随机森林的云计算用户公共安全信誉模型。 Aiming to solve these problems, cloud computing users’ public safety trust model based on scorecard-random forest was proposed.
45450 首先，利用 Word2Vec 和卷积神经网络进行公共安全标签分类； Firstly, the text was processed using Word2Vec in the data preprocessing stage. The convolution neural network (CNN) was used to extract the sentence features for user content tag classification.
45451 其次，采用评分卡方法，筛选强相关性指标； Then,scorecard method was used to filter the strong correlation index.
45452 最后，结合随机森林算法，建立云计算用户公共安全信誉模型。 Meanwhile, in order to establish the users’ public safety trust evaluation model in cloud computing, a random forest method was applied.
45453 实验分析表明，所建立的模型能够解决云计算公共安全监管中用户信誉指标筛选不准确和信誉区分准确性低等问题， Experimental results show that the pro-posed users’ public safety trust evaluation model outperforms the general trust evaluation model.
45454 能够有效识别有害用户，提高云计算用户监管效率。 The proposed model can effectively distinguish malicious users from normal users, and it can improve the efficiency of the cloud computing users management.
45455 基于位置服务（LBS, location-based service）在为人们的生活带来便捷的同时，对用户的隐私信息带来了不可忽略的威胁。 Location-based service (LBS) brings a lot of conveniences in people’s daily life, but the conveniences are accompanied with the leaking of privacy.